Sift

Sift

Real-time fraud detection and prevention platform

About Sift

Simplify's Rating
Why Sift is rated
B+
Rated B on Competitive Edge
Rated A on Growth Potential
Rated B on Rating Differentiation

Industries

AI & Machine Learning

Financial Services

Company Size

51-200

Company Stage

Series A

Total Funding

$4.5M

Headquarters

Bristol, United Kingdom

Founded

2011

Overview

Sift provides a platform focused on detecting and preventing online fraud in real-time, catering to clients in e-commerce, fintech, and digital marketplaces. The platform uses machine learning and artificial intelligence to analyze large datasets, helping businesses identify and reduce fraudulent activities. One of its standout features is dynamic friction, which allows genuine users to navigate seamlessly while blocking potential fraudsters. Sift also offers actionable insights that assist businesses in making informed decisions. Revenue is generated through subscription fees based on transaction volume and service levels, and additional services like chargeback management and dispute resolution enhance its offerings. Sift's goal is to create a safer online environment for businesses and their customers.

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Simplify's Take

What believers are saying

  • Growing demand for AI-driven fraud detection in QSRs presents expansion opportunities for Sift.
  • Digital-first banks' need for effective authentication aligns with Sift's fraud prevention solutions.
  • Global trend towards secure payment systems supports Sift's mission for digital trust and safety.

What critics are saying

  • Rise of app-enabled friendly fraud challenges Sift's mobile fraud detection capabilities.
  • Reliance on third-party delivery apps by QSRs introduces new fraud risks for Sift.
  • Complex payment processes may complicate Sift's integration and effectiveness in fraud prevention.

What makes Sift unique

  • Sift offers a comprehensive platform for real-time online fraud detection and prevention.
  • The company uses machine learning and AI to analyze vast amounts of data effectively.
  • Sift's dynamic friction feature ensures seamless user experience while blocking fraudsters.

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Funding

Total Funding

$4.5M

Below

Industry Average

Funded Over

6 Rounds

Series E funding typically includes additional rounds after Series D if the company needs more capital. The business is usually stable, and these rounds are typically used for further expansion or to address market challenges.
Series E Funding Comparison
Below Average

Industry standards

$100M
$245M
Stripe
$250M
Reddit
$1250M
Epic Games
$1500M
Airbnb

Company News

SpaceNews
Jun 25th, 2024
Sift raises $17.5M in Series A

Southern California startup Sift raised $17.5 million in a Series A funding round led by Google Ventures. Announced on June 25, the investment will help Sift expand its staff and accelerate the development of its platform, which aids engineers in analyzing hardware sensor data. Sift's automated data review product generates reports to highlight potential issues, benefiting industries like aviation, defense, energy, and transportation.

GlobeNewswire
Nov 17th, 2021
Sift Acquires Passwordless Authentication Pioneer Keyless to Provide Regulated Businesses and Online Merchants with Secure, Frictionless Authentication

Biometric authentication innovator eliminates password-based account takeover and enables PSD2 Strong Customer Authentication while preserving user privacy

TechCrunch
Apr 22nd, 2021
Fraud prevention platform Sift raises $50M at over $1B valuation, eyes acquisitions

With the increase of digital transacting over the past year, cybercriminals have been having a field day.

PYMNTS
Oct 8th, 2020
The Ordering Innovations Attracting Restaurant Customers

This Deep Dive explores how restaurants are using innovative dining and ordering technology to satisfy customer needs amid the COVID-19 pandemic.

PYMNTS
Sep 22nd, 2020
Deep Dive: How QSRs Can Fight The Rise Of App-Enabled Friendly Fraud

This Deep Dive examines how the increased use of mobile apps has led to a rise in friendly fraud and how AI and machine learning can help fight it.

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